Results 11 to 20 of about 462,780 (278)

Towards MR contrast independent synthetic CT generation

Zeitschrift für Medizinische Physik
The use of synthetic CT (sCT) in the radiotherapy workflow would reduce costs and scan time while removing the uncertainties around working with both MR and CT modalities.
Attila Simkó, Mikael Bylund, Gustav Jönsson, Tommy Löfstedt, Anders Garpebring, Tufve Nyholm, Joakim Jonsson   +6 more
doaj   +4 more sources

Synthetic CT generation from cone-beam CT using deep-learning for breast adaptive radiotherapy

Journal of Radiation Research and Applied Sciences, 2022
We investigated the feasibility of the generation of synthetic CT (sCT) from CBCT images with deep learning and the dose evaluation for CBCT-guided breast cancer adaptive radiotherapy.A total of sixty-eight patients receiving radiotherapy after breast ...
Xuetao Wang, Wanwei Jian, Bailin Zhang, Lin Zhu, Qiang He, Huaizhi Jin, Geng Yang, Chunya Cai, Haoyu Meng, Xiang Tan, Fei Li, Zhenhui Dai   +11 more
doaj   +2 more sources

Generation of Synthetic-Pseudo MR Images from Real CT Images

Tomography, 2022
This study aimed to generate synthetic MR images from real CT images. CT# mean and standard deviation of a moving window across every pixel in the reconstructed CT images were mapped to their corresponding tissue-mimicking types.
Isam F. Abu-Qasmieh, Ihssan S. Masad, Hiam H. Al-Quran, Khaled Z. Alawneh   +3 more
doaj   +3 more sources

Comparison of Supervised and Unsupervised Approaches for the Generation of Synthetic CT from Cone-Beam CT [PDF]

Diagnostics, 2021
Due to major artifacts and uncalibrated Hounsfield units (HU), cone-beam computed tomography (CBCT) cannot be used readily for diagnostics and therapy planning purposes.
Matteo Rossi, Pietro Cerveri
doaj   +4 more sources

Incorporating the synthetic CT image for improving the performance of deformable image registration between planning CT and cone-beam CT

Frontiers in Oncology, 2023
ObjectiveTo develop a contrast learning-based generative (CLG) model for the generation of high-quality synthetic computed tomography (sCT) from low-quality cone-beam CT (CBCT). The CLG model improves the performance of deformable image registration (DIR)
Na Li, Na Li, Na Li, Xuanru Zhou, Xuanru Zhou, Shupeng Chen, Jingjing Dai, Tangsheng Wang, Chulong Zhang, Wenfeng He, Yaoqin Xie, Xiaokun Liang   +11 more
doaj   +3 more sources

Abdominopelvic MR to CT registration using a synthetic CT intermediate

Journal of Applied Clinical Medical Physics, 2022
AbstractAccurate coregistration of computed tomography (CT) and magnetic resonance (MR) imaging can provide clinically relevant and complementary information and can serve to facilitate multiple clinical tasks including surgical and radiation treatment planning, and generating a virtual Positron Emission Tomography (PET)/MR for the sites that do not ...
Heo, Jin Uk, Zhou, Feifei, Jones, Robert, Zheng, Jiamin, Song, Xin, Qian, Pengjiang, Baydoun, Atallah, Traughber, Melanie S., Kuo, Jung‐Wen, Helo, Rose Al, Thompson, Cheryl, Avril, Norbert, DeVincent, Daniel, Hunt, Harold, Gupta, Amit, Faraji, Navid, Kharouta, Michael Z., Kardan, Arash, Bitonte, David, Langmack, Christian B., Nelson, Aaron, Kruzer, Alexandria, Yao, Min, Dorth, Jennifer, Nakayama, John, Waggoner, Steven E., Biswas, Tithi, Harris, Eleanor, Sandstrom, Susan, Traughber, Bryan J., Muzic, Raymond F.   +30 more
openaire   +2 more sources

Automatic online quality control of synthetic CTs [PDF]

Medical Imaging 2020: Image Processing, 2020
Accurate MR-to-CT synthesis is a requirement for MR-only workflows in radiotherapy (RT) treatment planning. In recent years, deep learning-based approaches have shown impressive results in this field. However, to prevent downstream errors in RT treatment planning, it is important that deep learning models are only applied to data for which they are ...
van Harten, Louis D., Wolterink, Jelmer M., Verhoeff, Joost J. C., Išgum, Ivana   +3 more
openaire   +2 more sources

MRI‐based synthetic CT in the detection of knee osteoarthritis: Comparison with CT

Journal of Orthopaedic Research, 2023
AbstractMagnetic resonance Imaging is the gold standard for assessment of soft tissues; however, X‐ray‐based techniques are required for evaluating bone‐related pathologies. This study evaluated the performance of synthetic computed tomography (sCT), a novel MRI‐based bone visualization technique, compared with CT, for the scoring of knee ...
Saeed Arbabi, Wouter Foppen, Willem Paul Gielis, Marijn van Stralen, Mylène Jansen, Vahid Arbabi, Pim A. de Jong, Harrie Weinans, Peter Seevinck   +8 more
openaire   +5 more sources

SynthRAD2023 Grand Challenge dataset: Generating synthetic CT for radiotherapy [PDF]

Medical Physics, 2023
AbstractPurposeMedical imaging has become increasingly important in diagnosing and treating oncological patients, particularly in radiotherapy. Recent advances in synthetic computed tomography (sCT) generation have increased interest in public challenges to provide data and evaluation metrics for comparing different approaches openly.
Thummerer, Adrian, van der Bijl, Erik, Galapon, Arthur Jr, Verhoeff, Joost JC, Langendijk, Johannes A, Both, Stefan, Cornelis, Berg, AT van den, Maspero, Matteo   +8 more
openaire   +6 more sources

Synthetic MRI Generation from CT Scans for Stroke Patients

BioMedInformatics, 2023
CT scans are currently the most common imaging modality used for suspected stroke patients due to their short acquisition time and wide availability. However, MRI offers superior tissue contrast and image quality.
Jake McNaughton, Samantha Holdsworth, Benjamin Chong, Justin Fernandez, Vickie Shim, Alan Wang   +5 more
doaj   +1 more source